A census of amplified and overexpressed human cancer genes

Key Points Integrated screens of DNA copy number and gene expression in human cancers using microarray platforms have accelerated the rate of discovery of amplified and overexpressed genes. However, the biological importance of most of the genes identified in such studies remains unclear. Amplification events often include multiple genes, so consideration of the pattern of genetic alteration alone is usually insufficient to identify which gene in an amplicon is being selected for owing to its contribution to oncogenesis. Supplementary datasets are usually required, including physical mapping, determination of overexpression, correlation with clinical outcome, biological investigations of function and, in some cases, efficacy of drugs targeted against the encoded overexpressed proteins. In this Analysis we propose a weight-of-evidence based classification system for identifying individual genes in amplified regions that are selected for in an amplicon and so contribute to cancer development. The proposed classification scheme takes into account the complex and sometimes distinct datasets that are available for different amplicons in cancer. Using this classification scheme in a census of the published literature, we have identified 77 genes for which there is evidence of involvement in human cancer development. The 77 genes were divided into three classes based on the weight of supporting evidence. We consider that for class II (12 genes), and class I (3 genes) the evidence is sufficiently strong for their inclusion in the census of human cancer genes. Linking newly generated integrated datasets to supporting evidence using the criteria outlined in this Analysis will aid in the future identification of amplified and overexpressed genes that contribute to cancer development. This article proposes a weight-of-evidence based classification system for identifying individual genes in an amplified region of the genome that contribute to cancer development. The 77 genes identified using this approach have been further subdivided into different gene classes. Integrated genome-wide screens of DNA copy number and gene expression in human cancers have accelerated the rate of discovery of amplified and overexpressed genes. However, the biological importance of most of the genes identified in such studies remains unclear. In this Analysis, we propose a weight-of-evidence based classification system for identifying individual genes in amplified regions that are selected